Simulating bio-economic management scenarios for the sea bass (Dicentrachus labrax) fishery in France

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18 th World IMACS / MODSIM Congress, Cairns, Australia 13-17 July 29 http://mssanz.org.au/modsim9 Simulating bio-eonomi management senarios for the sea bass (Dientrahus labrax) fishery in Frane Bruno Drouot 1, Olivier Thébaud 2, Eri Ramat 3, Yvon Morizur 4, Jean-Pierre Boude 2 1 Agroampus Ouest, Fisheries and Aquati Sienes Center, Rennes, Frane 2 Ifremer, UMR-Amure, Marine Eonomis Department, Plouzané, Frane. Email : olivier.thebaud@ifremer.fr 3 Université du Littoral Côte d Opale, Laboratoire d Informatique du Littoral, Calais, Frane 4 Ifremer, Fisheries Siene and Tehnology Department, Plouzané, Frane Abstrat: The fishery for ommon sea bass (Dientrarhus labrax) is the fourth most important Frenh metropolitan fishery in value terms, with approximately 5 5 tons landed, and a total turnover of about 52 million euro in 26. Given its high market value, sea bass is targeted by a range of métiers, resulting in interations between a large number of fleets. The annual ontributions to athes and landings of eah of these fleets are highly variable, as are their level of eonomi dependene towards the speies. Sea bass is also an emblemati speies for rereational fishermen. Currently, there is no limitation on total allowable ath in this fishery, nor are ath alloations speified at the individual vessel level. The fishery thus faes the traditional diffiulties of ommon-pool resoure management, with a potential for the development of exess apaity and a risk of overexploitation. The nature and strength of externalities between fishing agents an thus be very different aording to the fleets onsidered, and may lead to variable levels of potential support towards management deisions aimed at takling these externalities. The aim of this paper is to simulate the response of Frenh fishing fleets to the introdution of alternative management senarios for the sea bass (Dientrarhus labrax) fishery. The analysis is based on a bioeonomi model whih inludes and age-strutured model of population dynamis and a detailed representation of the numerous fishing fleets whih impat the stok, inluding the size distribution of athes per fleet and per fishing tehnique, and the eonomi status of fishing vessels. The main emphasis of the analysis is on the heterogeneity of ommerial fleets in terms of both their harvesting apaity and their reliane on sea bass for their revenue; rereational fishing is also inluded in the analysis and adds to the heterogeneity of behaviors whih are aounted for in the model. Simulation results emphasize the diversity of antiipated impats of alternative management senarios from both a short-term and a long-term perspetive, and the assoiated heterogeneity of eonomi inentives for different fleets to support these management senarios. Keywords: Bio-eonomi modeling, sea-bass fisheries, management senarios 211

Drouot et al., Simulating bio-eonomi management senarios for the sea bass (Dientrahus labrax) fishery in Frane. 1. INTRODUCTION The fishery for ommon sea bass (Dientrarhus labrax) is the fourth most important Frenh metropolitan fishery in value terms, with approximately 5 5 tons landed, and a total turnover of about 52 million euro in 26. It thus onstitutes an important resoure for the Frenh fishing fleet, whih is the primary ontributor to the landings of this speies at the European sale. Given its high market value, sea bass is targeted by a range of métiers, resulting in interations between a large number of fleets. The annual ontributions to athes and landings of eah of these fleets are highly variable, as are their level of eonomi dependene towards the speies. Sea bass is also an emblemati speies for rereational fishermen, whih have been estimated to ath at least as muh of this speies as ommerial fishing firms aording to reent studies (Fritsh, 25). Currently, there is no limitation on total allowable ath in this fishery, nor are ath alloations speified at the individual vessel level. The fishery thus faes the traditional diffiulties of ommon-pool resoure management, with a potential for the development of exess apaity and a risk of overexploitation. The heterogeneity of the fleets involved in the fishery however reates a partiular situation ompared to the traditional representation of open aess fisheries. This representation usually assumes that the eonomi agents involved in a fishery are homogeneous in terms of both their athing apaity and their eonomi dependene with respet to the exploited fish stok. Hene, the interations between owners an be desribed as rossed negative externalities, implying a ertain symmetry with respet to the eonomi inentives whih drive their behavior (Clark, 26). This representation does not apply to the sea bass fishery: in this fishery, the status of eonomi agents varies strongly, from those who are strongly dependent on the speies for their eonomi viability but who have only limited impats on the fish stok, to those who weakly depend on the speies in eonomi terms but who strongly ontribute to athes. The nature and strength of externalities between fishing agents an thus be very different aording to the fleets onsidered, and may lead to variable levels of potential support towards management deisions aimed at takling these externalities. Theoretial bio-eonomi models aimed at expliitly taking into aount the diversity of uses of a ommonpool resoure, inluding rereational uses were developed as early as the 197s (Anderson, 1979; MConnel, Sutinen, 1979; Sutinen, 1979). Aording to Anderson (22), a key diffiulty in moving from suh models to applied simulation exerises lies in the frequent lak of biologial and eonomi data at the required resolution. The Fisheries Information system of Ifremer (www.ifremer.fr/sih) ollets extensive sets of data onerning fishing fleets, their ativity, their prodution and their eonomi status, whih make it possible to develop applied models of the interations between the fleets exploiting the sea bass. The existene of a speifi study of the rereational fishing of this speies also allows to inlude this important omponent in the analysis (Morizur et al., 25). The aim of this paper is to simulate the response of Frenh fishing fleets to the introdution of alternative management senarios for the sea bass (Dientrarhus labrax) fishery. The analysis is based on a bioeonomi model whih inludes and age-strutured representation of population dynamis and a detailed representation of the numerous fishing fleets whih impat the stok, inluding the size distribution of athes per fleet and per fishing tehnique (metier), and the eonomi status of fishing vessels. The main emphasis of the analysis is on the heterogeneity of ommerial fleets in terms of both their harvesting apaity and their reliane on sea bass for their revenue; rereational fishing is also inluded in the analysis and adds to the heterogeneity of behaviors whih are aounted for in the model. The paper is strutured as follows. Setion 2 presents a brief overview of the fishery. Setion 3 presents the model developed and the simulated senarios. Setion 4 presents and disusses the results. Setion 5 onludes. 2. THE FRENCH FISHERY FOR SEA BASS The overall landings of ommon sea bass by European ommerial fishing fleets were estimated to be approximately 8. tons in 26 (ICES, 27). Frane was the main ontributing ountry with 5.5 tons, followed by the United Kingdom (approximately 6 tons), other ountries of the European Union inluding Portugal, Spain, the Netherlands and Denmark (approximately 8 tons in total), and estimated unreported landings. Between 1998 and 26, the landed quantities of ommon sea bass doubled in Europe. This inrease in landings primarily resulted from and inrease in bass fishing by Frenh ommerial fishing fleets. This inrease has raised the question of the level of exploitation of sea bass stoks, whih were onsidered as fully exploited at the end of the 198s (Pawson, Kelley, Pikett, 1987), partiularly as there is a strong suspiion of high undelared ath rates (Ulrih, 2). In a 26 report, ICES sientists in harge of 212

Drouot et al., Simulating bio-eonomi management senarios for the sea bass (Dientrahus labrax) fishery in Frane. assessing the status of ommon sea bass stoks noted that there had been a probable inrease in fishing mortality in reent years. This inrease did not put the stok at risk, however, as it had benefited from environmental hanges. In fat, the stok had ontinued expanding, both in size and in terms of its spatial distribution. The sientists reommended limiting the entry of new vessels in the pelagi trawl and mixed trawl fleets, as well as taking measures to protet juvenile fish. Based on the data olleted by the Fisheries Information System of Ifremer, the number of ommerial fishing vessels having landed or targeted ommon sea bass in the North Sea, English Channel and Atlanti was estimated to be 2.498 in 24, or two thirds of the Frenh fleet fishing in this maritime region. Bass is aught using a variety of gears, inluding hook-and-line, longline, bottom trawl, pelagi trawl, and nets. Subfleets of vessels were identified, based on the main gears they use and their ativity profile. The most important sub-fleets inlude polyvalent trawlers (58 vessels), netters (453 vessels) and bottom-trawlers (446 vessels). Other sub-groups inlude the pot-hook-andline sub-fleet (73 vessels), the hook-and-line sub-fleet (73 vessels), the long-liners (69 vessels), the pelagi trawlers (58 vessels), the line and long-line sub-fleet (46 vessels) and the purse seiners (3 vessels). These fleets differ strongly in terms of (i) the spatial and temporal distribution of their ativity, (ii) the size struture of fish landed (depending on the gears, areas and seasons fished), and (iii) the pries at first sale for bass landed, whih hange with the size of fish landed, but also with the gear used to ath it. In addition, ommon sea bass is an important target speies for rereational fishers. This ativity is not subjet to liensing, hene no register is available to desribe the population of rereational fishers. A reent study based on stratified sampling of the entire Frenh metropolitan population estimated that approximately 7. rereational fishermen were involved in the rereational fishery for sea bass, with a total ath of approximately 5. tons per year. 3. THE MODEL The sea bass model was developed based on a modeling tool that aims to quikly generate standard bio-eonomi models based on a similar representation of a fishery (Versmisse et al., 27). Implemented in the Virtual Environment Laboratory simulation platform 1, the tool was used to generate a disrete-time model of the sea bass fishery using the following assumptions as regards the desription of the fishery. The model was then alibrated based on data olleted by Ifremer onerning the ativity, landings, returns and Tehnial module Key model omponents We onsider that there is only one stok of ommon bass, with the age lass of fish ( = 1 to 15+.), and t the simulation year. () F t, the fishing mortality per age lass assoiated to eah fleet f,m, and metier, is defined as F () t = E (t)q (t)nbvessels () t with E () t a f,m, f f,m, f,m, f,m, measure of nominal fishing effort per vessel and metier assumed onstant over the simulation period, q () t the athability f,m, oeffiient per fleet and metier, and nbvessels () t the number of f vessels per fleet. Stok dynamis Total annual mortality of fish belonging to a given age lass is written: () () () with () Z t = M t + F t f,m, f,m M t the natural death rate, variable aording to age but onstant over the simulation period. The number of fish that reahes age, < 15, is defined as 1 t N t+ 1 = N t e. For age group 15+, the number of ( ) ( ) () 1 ( fish is written: ( 1() t 1) ( ) () t ) N t+ = N t e +N t e. 1 Reruitment is exogenous, and assumed onstant. Fish biomass per age lass is written B () t = N (t)w with W the average weight of fish at age. Cathes and landings Annual athes in numbers of fish per age lass by metier and fleet 1 (t) e are written C () t = F. N (t). f, m, f, m, Z (t) Landings in weight per age lass, per metier are thus expressed L (t) = ( 1 d )C (t)w with d a disard rate, assumed f,m, f,m, f,m, f,m, to be nil in the simulations presented in this study due to lak of empirial information. Eonomi returns Gross turnover assoiated to landings is alulated as follows: G () t = L (t)p with p the prie of bass per age lass, f,m, f,m, f,m, f,m, per fleet and metier. Net returns are then alulated as: () 1 NR t =( LC ) G (t) f,m f,m with LC the landing osts. f,m, f,m 1 http://vle.univ-littoral.fr/fr/index.php/aueil 213

Drouot et al., Simulating bio-eonomi management senarios for the sea bass (Dientrahus labrax) fishery in Frane. osts of fishing vessels operating in the North-East Atlanti region, and has involved ompilation and indepth analysis of a large set of data. 3.1. The biologial module The model is based on an aged-strutured representation of the dynamis of a single population of ommon sea bass (Beverton and Holt, 1957) and on the expliit representation of fishing mortality by the main Frenh sub-fleets involved in the fishery (fishing mortality due to other fleets being regarded as a foring fator). The population of ommon sea bass is assumed to form one stok. Reruitment is assumed onstant, and ours one per simulation year at the beginning of the year. Natural mortality varies aording to eah age lass, but is assumed onstant over the simulation period. Data used for alibration of the biologial module was taken from Fritsh (25), and is based on pseudo-ohort analysis. 3.2. The tehnial module The tehnial module explains fishing mortality rates for eah gear and fleet, whih lead to the observed levels of athes and landings (disards being assumed to be nil in the simulations, given the lak of empirial information on the nature and extent of these in the various sub-fleets). The nominal effort of eah sub-fleet with eah of the five gears used (line, longline, bottom trawl, pelagi trawl, net) is desribed. The size struture of athes speifi to eah sub-fleet is alulated, based on the ombination of gears used by eah fleet and a athability oeffiient for eah gear and eah age-lass. This allows alulation of the fishing mortality assoiated with the nominal effort of eah fleet. The size struture of athes for eah gear and age lass were derived from the data olleted at landing sites (Fritsh, 25). The demographi struture of landings by rereational fishers is based on data presented in Morizur and al. (25). 3.3. The eonomi module From an eonomi perspetive, eah fleet is haraterized in terms of its ost struture, and the share of sea bass landings in its total turnover. The analytial approah to the modeling of stok dynamis and athes allows the model to represent the eonomi tradeoffs assoiated to hanges in the omposition of landings, larger fish being sold at higher pries. Turnover assoiated to landings of sea bass is thus defined, for eah fleet, as the produt of quantities of fish landed per age group, multiplied by the prie at first sale of fish in that age lass. Differenes in average pries of fish of the same age lass aught by different fleets using alternative metiers are also inluded in the model. Landing osts are deduted from gross turnover to obtain net turnover. Shared osts, inluding osts whih are a funtion of nominal fishing effort (fuel and oil), and other expenses (e.g. ie osts, bait, food) are deduted from net turnover before determining the alloation of net returns to vessel-owners and rews. Eonomi parameters were estimated based on the eonomi survey arried out sine 21 by Ifremer (Leblond and Al, 25). 3.4. Simulation senarios In 26, the British Department of Environment Food and Rural Affairs launhed a onsultation on the potential effets of introduing new management measures in the sea bass fishery, with the aim to improve the produtive and reprodutive apaity of the stok. As part of the onsultation, several measures were proposed for assessment, inluding an inrease in the minimum landing size of fish from 36m to 45m, throughout the entire fishery. Justifiation for suh a measure rested in (i) the ensuing inrease in the number of spawning fish in the stok by limiting the ath of juvenile fish; (ii) an inrease in the potential ath of larger fish by rereational fishers; and (iii) an improvement in the size struture of landings by ommerial fishers towards higher pries paid for the fish landed. In Ireland, a minimum landing size of 4m was adopted in 199 [Bass (Conservation off Stoks) Order, 199]. Cath (Number) 3 2 5 2 1 5 1 5 1 2 3 4 5 6 7 8 9 1 11 12 13 14 15+ Age groups Line Net Longline Pelagi traw l Bottom traw l Rereational Figure 1 Demographi struture of landings per main gear (medium values 23-25) 214

Drouot et al., Simulating bio-eonomi management senarios for the sea bass (Dientrahus labrax) fishery in Frane. The bio-eonomi model was used to simulate two senarios derived diretly from these poliy orientations as regards management of the sea bass fishery. The first senario simulates an inrease from a minimum landing size of 36m to 4m, whih protets fish up to 4 years from the fishery given the growth parameters estimated for the stok. The seond senario onsiders an inrease of the minimum size to 45m, whih protets fish aged 7 years or less. In pratie, this amounts to removing age groups 4, 5 and 6 from the landings of ertain fleets (see fig 1). In terms of numbers of fish aught, rereational fishing largely dominates the landings, although this an inlude a variety of fishing gears (Fritsh, 25). Whereas ommerial fishers harvest mainly age groups 5 to 8, rereational fishermen also ath younger fish (age group 4), and would be diretly affeted by the first senario. Trawling fleets would be strongly impated by senario 2. The model assumes that reduing fishing mortality of younger fish an be ahieved by improving the seletivity of fishing gears. We thus assume that there would be no disards, resulting from tehnial diffiulties to atually avoid the ath of the smaller fishes. If suh disarding takes plae, the longer term benefits of inreasing minimum lading sizes would be strongly eroded. 4. RESULTS Based on simulation results, the omponents of the fishery for whih investments in inreased gear seletivity ould positively impat on the overall status of fleets an be identified, as well as the distribution of osts and benefits indued in the short and long-term by suh investments. 4.1. Global impats of the two senarios Landings in tonnes Gross return (euros thousands) 12 1 8 6 4 2 5 45 4 35 3 25 2 15 1 5 2 4 6 8 1 12 14 16 18 2 22 24 26 28 3 Years 2a 2 4 6 8 1 12 14 16 18 2 22 24 26 28 3 Years 2b S enario 1 S enario 2 Senario 1 Senario 2 Figure 2 Effets of the two management senarios on quantities landed (a) and gross turnover of the fishery (b). Size limit hanged in year 8. First, simulation results an be onsidered at the sale of the entire fishery. Figure 2 illustrates the lassial tradeoff between short-term osts and longer-term benefits assoiated to the adoption of seletivity measures. Following a period of stok reovery after the inrease of size limits, landings are restored in the longterm due to the inrease in ath rates, all else equal. Higher size limits in senario 2 leads to long-term results similar to those obtained with senario 1 in terms of total ath. The two senarios however differ with respet to transitional periods. While both are haraterized by short-term losses, the intensity and duration of these transitional periods are proportional to the effort made to inrease seletivity (Maher, 28). The first senario leads to a short-term drop in landings by 28% ompared to the status quo, whereas the redution is muh stronger in the seond senario leading to a 58% derease in the first year, 54% in the seond, 47% in the third year, et. (figure 2a). Figure 2b illustrates the simulated impats of the two management senarios on the total gross return of the fleets modeled. In the long run, the first senario leads to an inrease of turnover by 12% ompared to the status quo, while the seond senario results an inrease of 43%, all else equal. These higher levels of returns are observed despite an overall level of athes omparable to that observed with the status quo. This is due to the hange whih the management measures entail in the size struture of landings, and to the fat that fish aged 6 years and more feth higher pries at first sale than the smaller fish. 4.2. Distribution of the impats of the management senario Figure 3 illustrates the heterogeneity of the impats of the management senarios among sub-fleets in terms of landings. In the short term ( hange in t, defining the immediate effet of the management measure in the year following its adoption), the main impat of the onservation measures is to strongly redue the landings 215

Drouot et al., Simulating bio-eonomi management senarios for the sea bass (Dientrahus labrax) fishery in Frane. of bottom trawlers and rereational fishers, while the redution is very limited for the hook-and-line subfleet, due to the size struture of athes by these three sub-fleets. In the longer term ( hange in t+2 ), and under the assumption that nominal fishing effort would remain stable aross sub-fleets and gears, and that gear seletivity is only modified for 15% smaller fish, landings inrease partiularly 1% for the hook-and-line sub-fleet, and to a 5% Change in t (%) lesser degree for trawlers and rereational Change in t+2 (%) % fishers. -5% -1% Inreased size limits would therefore negatively impat landings mainly of trawler and rereational sub-fleets, with expeted benefits would mainly go to the hook-and-line and longline sub-fleets. This result is however dependent on the 3a - Senario 1 apaity for hook-and-line fishers to 15% atually ath the sea bass whih have 1% been allowed to grow due to greater size 5% Change in t (%) limits, whih remain further away from % Change in t+2 (%) -5% the oast than younger fish, hene are less -1% aessible to the smaller vessels urrently operating in the hook-and-line sub-fleet. Given that fish aessibility to the fleets is seasonally and spatially heterogeneous, materialization of the effets desribed in these simulations as regards inreased 3b - Senario 2 ath of larger sized fish would also require spatial and seasonal Figure 3 Effets of the two management senarios on onentrations of fishing effort whih seleted fleets (hanges in landings in %) ould entail ongestion problems, not aounted for in the urrent version of the model. Figure 4 illustrates the impats of the first senario on the gross turnover of sub-fleets. The immediate effets on the turnover are mainly negative for a number of fleets, with small benefits for others. The most negatively impated sub-fleets in the short term are the bottom trawlers, the long-liners and the netters and hook-and-line sub-fleet. In the longer term, all the sub-fleets see their turnover improve ompared to the status quo. There are however signifiant differenes between sub-fleets, with those using nets or hook-and-line taking partiular advantage of the hange in the struture of the sea bass stok. The eonomi onsequenes of these modifiations for the sub-fleets strongly relate to the importane of sea bass athes in the remuneration of ommerial fishing firms and in Gross retu rn (euros thousan ds) 14 12 1 8 6 4 2-2 -4 Bottom Trawlers 16-2m Bottom Trawlers 24-4m Bottom Trawlers 2-24m Mixed Trawlers 16-2m Netters 12-2m Netters <12m Mixed Trawlers 2-4m Pelagi trawlers 16-24m Longliners <12m Liners longliners <12m Liners <12m Netters hook and line <12m the utility derived from fishing trips by rereational fishers. 5. CONCLUSION Due to the fat that sea bass is aught by a large number of ommerial fishing vessels and rereational fishers, introdution of onservation measures aimed at improving the size struture of athes of this speies an potentially impat a large number of stakeholders. The distribution of the short-term and longer-term impats is a key for prediting the degree of support whih may be expeted for the measure. The analysis shows that in the short term, seletivity measures imply a strong redution in the landings of bottom trawlers and rereational fishers, while the athes of hook-and-line fishers derease only slightly. In the long term, landings of the latter Bottom Trawlers 16-2m Bottom Trawlers 24-4m Bottom Trawlers 2-24m Rereational experimented Bottom Trawlers 24-4m Bottom Trawlers 2-24m Rereational non experimented Rereational experimented Change in t Change in t+2 Figure 4 Effets of the first senario of gross returns per fleets (hanges in %) R ereational non experimented Mixed Trawlers 2-4m Mixed Trawlers 16-2m Longliners <12m Netters <12m Pelagi trawlers 16-24m Bottom Trawlers 16-2m Mixed Trawlers 2-4m Mixed Trawlers 16-2m Netters <12m Netters 12-2m Pelagi trawlers 16-24m Longliners <12m Netters hook and line <12m Liners longliners <12m Netters 12-2m Liners <12m Liners longliners <12m Netters hook and line <12m Liners <12m 216

Drouot et al., Simulating bio-eonomi management senarios for the sea bass (Dientrahus labrax) fishery in Frane. would inrease muh more in relative value terms than the landings of the other sub-fleets. This allows an improvement in the total turnover generated by the same ommerial fleet, hene an improvement in the overall level of profit for firms operating in the fishery. Implementing suh management measures may involve adopting fishing tehniques whih would also affet the athes of other speies, and the benefits observed as regards athes of sea bass may be overrun by osts assoiated to redued revenue from these other speies. The model allows this to be aounted for, and evaluation of the overall onsequenes of suh measures is underway. REFERENCES Anderson L.G., 22, Report on the Bioeonomi Modelling Workshop, 34 p. http://www.asmf.org/researhstatistis/essbioeomodelwkshpreport.pdf Beverton, R.J.H., and Holt, S.J., 1957. On the dynamis of exploited fish populations. Fish.Invest.London,Ser.II 19: 1:533. Clark, C.W., 26. The worldwide risis in fisheries. Eonomi Models and Human Behavior. Cambridge University Press. 263p. Fritsh M., 25, Traits biologiques et exploitation du bar ommun Dientrarhus labrax (L.) dans les pêheries françaises de la Manhe et du golfe de Gasogne. - Brest : Université de Bretagne oidentale, Thèse de dotorat : Oéanologie biologique : Brest. Harty, C., 24, Planning strategies for mangrove and saltmarsh hanges in southeast Australia, Coastal Management, 32, pp 45 415. Leblond E., Daurès F., Berthou P., Bermell S., Merrien C., Planhot M., Demanèhe S., Brigaudeau C., 25, Synthèse des flottilles de pêhe, Mer du Nord Manhe Atlantique, Ifremer, Brest, 58 p. Maher, C., Guyader, O., Talide, C., Bertigna, M., 28, A Cost-Profit Analysis of Improving Trawl Seletivity in the Case of Disards: the Nephrops norvegius Fishery in the Bay of Bisay, Fisheries Researh. MConnel K.E, Sutinen J.G, 1979, Bioeonomi models of marine rereational fishing, Journal of Environmental Eonomis and Management, 6:127-139. Morizur Y., Fritsh M., Thébaud O., Drouot B., Guyader O., 25, Exploitation du bar ommun par les pêhes réréatives : analyse quantitative, Colloque Golfe de Gasogne, Ifremer Brest, 9 p. Pawson M.G., Kelley D.F., Pikett G.D, 1987, The distribution and migrations of bass, Dientrarhus Labrax, in waters around England and Wales as shown by tagging, Journal of the Marine Biologial Assoiation of the UK, 67, 183-217. Pelletier D., Mahévas S., 25, Fisheries simulation models for evaluating the impat of management poliies, with emphasis on marine proteted areas, Fish and Fisheries, 2, 6 (4) : 37-349. Quesnel G., Duboz R., Ramat E., Traoré M.K., 27, VLE : A multimodeling and Simulation Environment. Proeedings of the Summer Simulation Multionferene (SummerSim 7), San Diego, California, USA, July 15-18, pp 367-374. Sutinen J.G., 1979, Eonomi priniples of alloation in rereational and ommerial fisheries, in J.H. Grover (Ed) : Alloation of fishery resoures, proeeding of tehnial onsultations, Vihy, Frane, 198, FAO, Rome. Ulrih C., 2, Modélisation multi-flottilles et multi-métiers des pêheries artisanales de la Manhe. Evaluation plurispéifique des stoks, étude des interations tehniques et intégration dans la modélisation bioéonomique. Thèse de dotorat de l ENSAR, 35 pp. Versmisse D., Maher C., Ramat E., Soulié J.-C., Thébaud O., 28. Developing a bioeonomi simulation tool of fisheries dynamis: a ase study. In Proeedings of the International Congress on Modelling and Simulation, Christhurh, New Zealand, Deember 27. International Soiety for Computer Simulation. 217